Abstract
Abstract We describe the use of cubic splines in regression models to represent the relationship between the response variable and a vector of covariates. This simple method can help prevent the problems that result from inappropriate linearity assumptions. We compare restricted cubic spline regression to non‐parametric procedures for characterizing the relationship between age and survival in the Stanford Heart Transplant data. We also provide an illustrative example in cancer therapeutics.
Keywords
CovariateMultivariate adaptive regression splinesRegressionRegression analysisParametric statisticsSimple (philosophy)Computer scienceStatisticsSpline (mechanical)Nonparametric regressionMathematicsSmoothing splineApplied mathematicsEconometricsSpline interpolation
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Publication Info
- Year
- 1989
- Type
- article
- Volume
- 8
- Issue
- 5
- Pages
- 551-561
- Citations
- 2604
- Access
- Closed
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Cite This
Sylvain Durrleman,
Richard Simon
(1989).
Flexible regression models with cubic splines.
Statistics in Medicine
, 8
(5)
, 551-561.
https://doi.org/10.1002/sim.4780080504
Identifiers
- DOI
- 10.1002/sim.4780080504